chr7.21393_chr7_33252523_33258064_-_2.R 

fitVsDatCorrelation=0.853930857238086
cont.fitVsDatCorrelation=0.255560065536173

fstatistic=13125.8005307471,52,692
cont.fstatistic=3793.41067073626,52,692

residuals=-0.384794664243918,-0.0758935875789567,-0.00352479106083602,0.0745262744733071,0.948611789250477
cont.residuals=-0.520319857944603,-0.179165889706210,-0.051817820219766,0.138979599080052,1.34264980475851

predictedValues:
Include	Exclude	Both
chr7.21393_chr7_33252523_33258064_-_2.R.tl.Lung	61.2136585747433	64.8141447452473	61.0874935531855
chr7.21393_chr7_33252523_33258064_-_2.R.tl.cerebhem	63.8096838917172	69.3272916997365	49.2228614361981
chr7.21393_chr7_33252523_33258064_-_2.R.tl.cortex	57.5122623947294	61.0104305909895	49.2155996397144
chr7.21393_chr7_33252523_33258064_-_2.R.tl.heart	61.2936350489418	69.9687135497116	53.1668478733079
chr7.21393_chr7_33252523_33258064_-_2.R.tl.kidney	62.544464528934	69.5783224985969	51.717918779388
chr7.21393_chr7_33252523_33258064_-_2.R.tl.liver	67.5794162849387	78.2118641856201	57.692007710736
chr7.21393_chr7_33252523_33258064_-_2.R.tl.stomach	64.2100181788601	70.4805780899788	56.9491767568102
chr7.21393_chr7_33252523_33258064_-_2.R.tl.testicle	62.3402928291905	70.6505561298465	51.6094734152042


diffExp=-3.60048617050403,-5.5176078080193,-3.49816819626012,-8.67507850076983,-7.03385796966285,-10.6324479006814,-6.27055991111872,-8.31026330065598
diffExpScore=0.981664318701217
diffExp1.5=0,0,0,0,0,0,0,0
diffExp1.5Score=0
diffExp1.4=0,0,0,0,0,0,0,0
diffExp1.4Score=0
diffExp1.3=0,0,0,0,0,0,0,0
diffExp1.3Score=0
diffExp1.2=0,0,0,0,0,0,0,0
diffExp1.2Score=0

cont.predictedValues:
Include	Exclude	Both
Lung	66.6154753444026	61.3039422367314	61.111564960174
cerebhem	61.67133577831	59.2462390762654	65.027968092981
cortex	61.4963444006337	64.0454280020807	69.8391775375131
heart	62.077664053045	65.9699528113127	63.6938982308715
kidney	57.9911614534342	66.4322197542627	59.6612408076183
liver	61.4521166756682	68.3064351737455	68.5287901686743
stomach	62.899425454727	65.2247260517552	67.050869192195
testicle	61.5962490239113	71.2274948554597	70.0918715503239
cont.diffExp=5.31153310767117,2.42509670204465,-2.54908360144696,-3.8922887582677,-8.44105830082849,-6.85431849807723,-2.32530059702825,-9.63124583154846
cont.diffExpScore=1.5369083750529

cont.diffExp1.5=0,0,0,0,0,0,0,0
cont.diffExp1.5Score=0
cont.diffExp1.4=0,0,0,0,0,0,0,0
cont.diffExp1.4Score=0
cont.diffExp1.3=0,0,0,0,0,0,0,0
cont.diffExp1.3Score=0
cont.diffExp1.2=0,0,0,0,0,0,0,0
cont.diffExp1.2Score=0

tran.correlation=0.93226670727703
cont.tran.correlation=-0.391107992811811

tran.covariance=0.00309602090584360
cont.tran.covariance=-0.000857334624289748

tran.mean=65.9090833263614
cont.tran.mean=63.5972631341091

weightedLogRatios:
wLogRatio
Lung	-0.236784004742258
cerebhem	-0.348103508347859
cortex	-0.241000207966445
heart	-0.553562236365055
kidney	-0.446461660527194
liver	-0.626314307014515
stomach	-0.392162483782801
testicle	-0.524976094610625

cont.weightedLogRatios:
wLogRatio
Lung	0.345449060617121
cerebhem	0.164550117074458
cortex	-0.168116702375150
heart	-0.252909211170195
kidney	-0.560992507684514
liver	-0.441079183171195
stomach	-0.151003330244460
testicle	-0.609185224453634

varWeightedLogRatios=0.0205238231037500
cont.varWeightedLogRatios=0.113117715270980

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.1567245192786	0.0728501047309231	57.0585935961486	7.34050811443386e-264	***
df.mm.trans1	0.213483209839600	0.065430047576328	3.26277020646453	0.00115749359845585	** 
df.mm.trans2	-0.181250084996027	0.0601718149617703	-3.01220904024888	0.00268810735240099	** 
df.mm.exp2	0.324798383821624	0.0824204849046174	3.94074827632357	8.94753564958822e-05	***
df.mm.exp3	0.093245338339981	0.0824204849046174	1.13133692974375	0.258305217101615	   
df.mm.exp4	0.216702106241106	0.0824204849046174	2.62922629600989	0.00874798876730628	** 
df.mm.exp5	0.258939434263095	0.0824204849046174	3.14168782873284	0.00175138999352742	** 
df.mm.exp6	0.344019096927911	0.0824204849046174	4.17395138266941	3.37540880856577e-05	***
df.mm.exp7	0.201750144930415	0.0824204849046174	2.44781555415373	0.0146199112680317	*  
df.mm.exp8	0.273061653859295	0.0824204849046174	3.31303139232073	0.000970938002738134	***
df.mm.trans1:exp2	-0.283263763795795	0.0789116064821028	-3.58963372339961	0.000354534438411559	***
df.mm.trans2:exp2	-0.257483598174949	0.0686837374205145	-3.74882916750019	0.000192502891118821	***
df.mm.trans1:exp3	-0.155617498177731	0.0789116064821028	-1.97204828434237	0.0490019135019052	*  
df.mm.trans2:exp3	-0.153724358133054	0.0686837374205145	-2.23814783391707	0.0255287242214276	*  
df.mm.trans1:exp4	-0.215396445440113	0.0789116064821028	-2.72959143835153	0.00650248802946425	** 
df.mm.trans2:exp4	-0.140177776036793	0.0686837374205145	-2.04091654445882	0.0416380593416668	*  
df.mm.trans1:exp5	-0.237432041949256	0.0789116064821028	-3.0088354873767	0.00271773961604176	** 
df.mm.trans2:exp5	-0.188010236433047	0.0686837374205145	-2.73733264225211	0.00635304373763503	** 
df.mm.trans1:exp6	-0.245085997016047	0.0789116064821028	-3.10582952168934	0.00197497232220355	** 
df.mm.trans2:exp6	-0.156121607599304	0.0686837374205145	-2.27305055698198	0.0233288567754168	*  
df.mm.trans1:exp7	-0.153961243952133	0.0789116064821028	-1.95105955658185	0.0514531542900845	.  
df.mm.trans2:exp7	-0.117936823795019	0.0686837374205145	-1.71709968362603	0.086408403863912	.  
df.mm.trans1:exp8	-0.25482402618237	0.0789116064821028	-3.22923379135824	0.00129988151578884	** 
df.mm.trans2:exp8	-0.186839535784854	0.0686837374205145	-2.7202878410785	0.00668628273577045	** 
df.mm.trans1:probe2	0.186517046138589	0.0394558032410514	4.72723986884975	2.75834729304796e-06	***
df.mm.trans1:probe3	-0.501190906139852	0.0394558032410514	-12.7025903661845	2.22043228938553e-33	***
df.mm.trans1:probe4	-0.353285739335717	0.0394558032410514	-8.95396140277141	3.13111674861016e-18	***
df.mm.trans1:probe5	-0.402799559599678	0.0394558032410514	-10.2088799748623	6.89030676263766e-23	***
df.mm.trans1:probe6	0.195237638183887	0.0394558032410514	4.94826165345316	9.41233866625921e-07	***
df.mm.trans1:probe7	-0.313520740954642	0.0394558032410514	-7.94612490941364	7.81635335362147e-15	***
df.mm.trans1:probe8	-0.0933976109468242	0.0394558032410514	-2.36714509083038	0.0182001236547259	*  
df.mm.trans1:probe9	-0.412740425504408	0.0394558032410514	-10.4608293736364	7.07350404222938e-24	***
df.mm.trans1:probe10	-0.498522123743397	0.0394558032410514	-12.6349505723588	4.47074375030562e-33	***
df.mm.trans1:probe11	-0.254440183497780	0.0394558032410514	-6.44873916121547	2.11704061461146e-10	***
df.mm.trans1:probe12	-0.199600423459732	0.0394558032410514	-5.05883563541446	5.40993414425549e-07	***
df.mm.trans1:probe13	-0.375894107182362	0.0394558032410514	-9.52696628391707	2.66413132238849e-20	***
df.mm.trans1:probe14	-0.226257003617707	0.0394558032410514	-5.73444170520144	1.46189520070165e-08	***
df.mm.trans1:probe15	-0.496510772696816	0.0394558032410514	-12.5839732539072	7.56468509955715e-33	***
df.mm.trans1:probe16	-0.409165858777898	0.0394558032410514	-10.3702326443119	1.61102096073640e-23	***
df.mm.trans1:probe17	-0.431283364169142	0.0394558032410514	-10.9307967077557	9.12682522515006e-26	***
df.mm.trans1:probe18	-0.382318409975835	0.0394558032410514	-9.6897890442148	6.60321376272615e-21	***
df.mm.trans1:probe19	-0.229238286458525	0.0394558032410514	-5.81000176470914	9.52960300904049e-09	***
df.mm.trans1:probe20	-0.315605313153091	0.0394558032410514	-7.99895800435061	5.28336292016262e-15	***
df.mm.trans1:probe21	-0.557882784035864	0.0394558032410514	-14.1394354748662	4.65217514557681e-40	***
df.mm.trans1:probe22	-0.324035700444505	0.0394558032410514	-8.21262460340347	1.06130695127382e-15	***
df.mm.trans2:probe2	0.239291655898967	0.0394558032410514	6.06480254468621	2.17323145518091e-09	***
df.mm.trans2:probe3	0.283781407892164	0.0394558032410514	7.19238704021381	1.65763861282794e-12	***
df.mm.trans2:probe4	0.454237782667932	0.0394558032410514	11.5125721783640	3.49164415918431e-28	***
df.mm.trans2:probe5	0.389868411625242	0.0394558032410514	9.88114243279698	1.25346101389981e-21	***
df.mm.trans2:probe6	0.397265597164995	0.0394558032410514	10.0686227254820	2.40470730946734e-22	***
df.mm.trans3:probe2	-0.09762816426544	0.0394558032410514	-2.47436767841198	0.0135859083759432	*  
df.mm.trans3:probe3	-0.132323296914585	0.0394558032410514	-3.35370936706492	0.00084081819524169	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.23369872425217	0.135343608643878	31.2811130623246	1.47412618850992e-134	***
df.mm.trans1	-0.0216390126461699	0.121558353078962	-0.178013374630978	0.858764569196237	   
df.mm.trans2	-0.0574947332548834	0.111789414794360	-0.514312856549495	0.607197480263597	   
df.mm.exp2	-0.173375841367359	0.153123813539751	-1.13225916570025	0.257917671913154	   
df.mm.exp3	-0.169704695604113	0.153123813539751	-1.10828415046009	0.268124162749997	   
df.mm.exp4	-0.0385830807747486	0.153123813539751	-0.251973092119551	0.801136677937179	   
df.mm.exp5	-0.0342897276202662	0.153123813539751	-0.223934650186625	0.822874249256517	   
df.mm.exp6	-0.0870716261390483	0.153123813539751	-0.568635433811504	0.569788059154222	   
df.mm.exp7	-0.0881558496473025	0.153123813539751	-0.575716131994172	0.564994236508972	   
df.mm.exp8	-0.0654068854887576	0.153123813539751	-0.427150316967372	0.669402716440504	   
df.mm.trans1:exp2	0.0962581771523403	0.146604889925985	0.65658230909581	0.51166780379544	   
df.mm.trans2:exp2	0.139233992437276	0.127603177949793	1.09114831365767	0.275587396381400	   
df.mm.trans1:exp3	0.0897455149268991	0.146604889925985	0.61215908263502	0.54063359388013	   
df.mm.trans2:exp3	0.213453188273928	0.127603177949793	1.67278896735561	0.0948208355994792	.  
df.mm.trans1:exp4	-0.0319675851526756	0.146604889925985	-0.218052652737673	0.82745237133566	   
df.mm.trans2:exp4	0.111938307279425	0.127603177949793	0.877237613341171	0.380662033011148	   
df.mm.trans1:exp5	-0.104356575262469	0.146604889925985	-0.711821927052736	0.476814948448633	   
df.mm.trans2:exp5	0.114627752251518	0.127603177949793	0.898314243369549	0.369330488433302	   
df.mm.trans1:exp6	0.00639299396994818	0.146604889925985	0.043606962722565	0.965230281024984	   
df.mm.trans2:exp6	0.195231456087767	0.127603177949793	1.52998898009094	0.126476433701450	   
df.mm.trans1:exp7	0.030755965963988	0.146604889925985	0.209788131756830	0.833894784304336	   
df.mm.trans2:exp7	0.150150329186928	0.127603177949793	1.17669741145481	0.239720898673850	   
df.mm.trans1:exp8	-0.0129290513776821	0.146604889925985	-0.0881897690057232	0.929751363395437	   
df.mm.trans2:exp8	0.215441641640354	0.127603177949793	1.68837206958218	0.0917903739760986	.  
df.mm.trans1:probe2	0.0357556961018635	0.0733024449629925	0.487783130834382	0.625857963724286	   
df.mm.trans1:probe3	-0.0158967094739150	0.0733024449629925	-0.216864655496015	0.828377741658014	   
df.mm.trans1:probe4	0.0308418961929880	0.0733024449629925	0.420748533129542	0.674069349847208	   
df.mm.trans1:probe5	0.0140601703393918	0.0733024449629925	0.191810387040845	0.84794700315382	   
df.mm.trans1:probe6	0.0731099040210336	0.0733024449629925	0.99737333533614	0.318931952419829	   
df.mm.trans1:probe7	0.00662860263704395	0.0733024449629925	0.090428124742503	0.927973175277546	   
df.mm.trans1:probe8	-0.052217443337986	0.0733024449629925	-0.712356093502046	0.476484402366046	   
df.mm.trans1:probe9	-0.0753760784452603	0.0733024449629925	-1.02828873557103	0.304173311172662	   
df.mm.trans1:probe10	-0.0168936306180446	0.0733024449629925	-0.23046476316818	0.817798755830213	   
df.mm.trans1:probe11	0.0115693639205555	0.0733024449629925	0.157830532479461	0.874636381548955	   
df.mm.trans1:probe12	0.0154706213684087	0.0733024449629925	0.211051914792464	0.832908896413179	   
df.mm.trans1:probe13	0.0258447119877124	0.0733024449629925	0.352576397700792	0.724513392209492	   
df.mm.trans1:probe14	-0.0824184155790898	0.0733024449629925	-1.12436107173096	0.261249741105879	   
df.mm.trans1:probe15	-0.0712157048760581	0.0733024449629925	-0.971532462689507	0.331622653614357	   
df.mm.trans1:probe16	-0.0254920943859729	0.0733024449629925	-0.347765949673887	0.728121717186895	   
df.mm.trans1:probe17	-0.035967131340034	0.0733024449629925	-0.490667553561036	0.623817149280352	   
df.mm.trans1:probe18	-0.0362146646368338	0.0733024449629925	-0.494044429965701	0.621431581767296	   
df.mm.trans1:probe19	-0.0868313759506815	0.0733024449629925	-1.18456316149508	0.236596889373158	   
df.mm.trans1:probe20	-0.05944102624994	0.0733024449629925	-0.81090100446103	0.417701321747072	   
df.mm.trans1:probe21	0.0116285280755447	0.0733024449629925	0.158637656375793	0.8740006428333	   
df.mm.trans1:probe22	0.00498481717222325	0.0733024449629925	0.0680034230064207	0.945802553227744	   
df.mm.trans2:probe2	-0.0677928296546416	0.0733024449629925	-0.924837223217692	0.35537297348064	   
df.mm.trans2:probe3	-0.104677794248449	0.0733024449629925	-1.42802595876981	0.153735528824342	   
df.mm.trans2:probe4	-0.147211424365112	0.0733024449629925	-2.00827440939294	0.045002251019833	*  
df.mm.trans2:probe5	-0.180596171962188	0.0733024449629925	-2.46371280048522	0.0139927917638141	*  
df.mm.trans2:probe6	-0.0429603359238206	0.0733024449629925	-0.586069618080401	0.5580198330014	   
df.mm.trans3:probe2	-0.0468628412969613	0.0733024449629925	-0.639308024727149	0.522834134298127	   
df.mm.trans3:probe3	-0.0787287113051479	0.0733024449629925	-1.07402572103693	0.283185514179911